CN116858999A - Carbon sink statistical method based on monitoring and evaluating carbon sink potential of mangrove ecological system - Google Patents
Carbon sink statistical method based on monitoring and evaluating carbon sink potential of mangrove ecological system Download PDFInfo
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Abstract
The invention provides a carbon sink statistical method based on monitoring and evaluating carbon sink potential of a mangrove ecological system, which comprises the following steps: acquiring ecological data in a mangrove ecological system; constructing a mangrove forest simulation ecological system according to the ecological data; adding carbon sink influence factor information into the mangrove forest simulated ecological system, acquiring current carbon sink potential monitored in the mangrove forest simulated ecological system, and carrying out carbon sink potential monitoring evaluation according to the influence factor information and the current carbon sink potential to determine a carbon sink potential evaluation result; and counting carbon sinks based on the evaluation result. The technical effect of accurately and effectively counting carbon sinks of the mangrove ecological system is achieved.
Description
Technical Field
The invention relates to the technical field of forestry carbon sinks, in particular to a carbon sink statistical method based on monitoring and evaluating carbon sink potential of a mangrove ecological system.
Background
The mangrove ecological system is an ecological function unity formed by mangrove plants growing on tropical coastal mud beaches and surrounding environments, has the functions of protecting coasts, purifying seawater, promoting siltation and the like, and is one of important components of the ecological system in China, so that the statistics of carbon sinks of the mangrove ecological system is an important link in the ecological development process. In the prior art, a technical scheme for carrying out carbon sink statistics on the mangrove ecological system is lacked, so how to accurately and effectively carry out carbon sink statistics on the mangrove ecological system is one of the problems to be solved in the technical field of forestry carbon sinks.
Disclosure of Invention
The present invention aims to solve at least some of the technical problems in the above-described technology. Therefore, the invention aims to provide a carbon sink statistics method based on monitoring and evaluating carbon sink potential of a mangrove ecological system, which is used for monitoring and evaluating carbon sink by collecting related data in the mangrove ecological system and constructing a simulation system, and the statistics of carbon sink is realized according to an evaluation result, so that the technical effect of accurately and effectively carrying out carbon sink statistics on the mangrove ecological system is realized.
The invention provides a carbon sink statistical method based on monitoring and evaluating carbon sink potential of mangrove ecological system, comprising the following steps:
acquiring ecological data in a mangrove ecological system;
constructing a mangrove forest simulation ecological system according to the ecological data;
adding carbon sink influence factor information into the mangrove forest simulated ecological system, acquiring current carbon sink potential monitored in the mangrove forest simulated ecological system, and carrying out carbon sink potential monitoring evaluation according to the influence factor information and the current carbon sink potential to determine a carbon sink potential evaluation result;
and counting carbon sinks based on the evaluation result.
Preferably, the method for acquiring ecological data in the mangrove ecological system based on the carbon sink statistical method for monitoring and evaluating the carbon sink potential of the mangrove ecological system comprises the following steps:
acquiring three-dimensional coordinates, characteristic information and connection information of a plurality of terrain points in the mangrove ecological system, and determining terrain data of the mangrove ecological system according to the three-dimensional coordinates, the characteristic information and the connection information;
collecting images of the mangrove ecological system through a remote sensing technology, carrying out image preprocessing on the images, determining image information data, and taking the image information data as image data of the mangrove ecological system;
acquiring soil data of the mangrove ecological system by accessing a preset soil information database;
acquiring climate data of a mangrove forest ecosystem by accessing a preset climate database;
acquiring rainfall data of the mangrove forest ecosystem by accessing a preset rainfall database;
acquiring plant data of the mangrove ecological system by accessing a preset plant database;
and determining ecological data in the mangrove ecological system according to the terrain data, the image data, the soil data, the climate data, the rainfall data and the plant data.
Preferably, the carbon sink statistical method based on monitoring and evaluating carbon sink potential of the mangrove ecological system collects images of the mangrove ecological system through a remote sensing technology, performs image preprocessing on the images, determines image information data, takes the image information data as image data of the mangrove ecological system, and comprises the following steps:
collecting an image of a mangrove ecological system through a remote sensing technology, and taking the image as a first image;
inputting the first image into a pre-trained image feature extraction network, carrying out feature extraction on the first image to obtain a feature region, marking the feature region, and determining the image subjected to region marking as a second image;
noise reduction processing is carried out on the second image, and a third image is obtained;
and carrying out sharpening processing on the third image to obtain a fourth image, determining image information data of the fourth image, and taking the image information data as image data of the mangrove ecological system.
Preferably, the method for calculating carbon sink based on monitoring and evaluating carbon sink potential of mangrove ecological system performs noise reduction treatment on the second image to obtain a third image, including:
respectively carrying out wiener filtering processing and Laplace filtering processing on the second image to obtain a first filtering image and a second filtering image;
image segmentation is carried out on the first filtering image to obtain a plurality of segmentation areas;
selecting any divided area, determining the midpoint of the divided area as a central pixel point, calculating the difference between gray values of the pixel points adjacent to the central pixel point in eight directions and the central pixel point, determining a correction matrix according to the difference between the gray values, the second image and the first filter image, and determining a gray correction value of the central pixel point according to the matrix characteristic value of the correction matrix;
correcting the pixel value of the central pixel point according to the gray correction value, and performing the above operation on all the pixel points in all the divided areas to obtain a first corrected image;
acquiring pixel values of all pixel points of the second filter image, and calculating a pixel mean value of the second filter image according to the pixel values of all pixel points;
performing multi-scale geometric transformation on the second filter image to obtain a frequency domain coefficient of the second filter image;
correcting each pixel value of the second filter image according to the pixel mean value and the frequency domain coefficient to obtain a second corrected image;
and carrying out image fusion on the first corrected image and the second corrected image to obtain a fused image, and taking the fused image as a third image.
Preferably, the carbon sink statistical method based on monitoring and evaluating carbon sink potential of the mangrove ecological system determines a correction matrix according to the difference of gray values, the second image and the first filter image, and determines a gray correction value of a central pixel point according to a matrix characteristic value of the correction matrix, including:
determining a minimum mean square error according to the second image and the first filtered image;
taking the opposite number from the square of the difference between the gray values of the central pixel point and the adjacent pixel points, dividing the opposite number by 2 times of the square of the minimum mean square error, and determining a first coefficient;
performing exponential operation on the first coefficient to determine a second coefficient;
multiplying the minimum mean square error with a preset coefficient, taking the reciprocal of the multiplied result, and determining a third coefficient;
taking the product obtained by multiplying the second coefficient and the third coefficient as a matrix element in the correction matrix, and performing the operation on each adjacent pixel point to determine the correction matrix;
and calculating a matrix characteristic value of the correction matrix, and taking the average value of the matrix characteristic value as a gray correction value of the central pixel point.
Preferably, the carbon sink statistical method based on monitoring and evaluating carbon sink potential of the mangrove ecological system corrects each pixel value of the second filtering image according to the pixel mean value and the frequency domain coefficient, and includes:
determining an enhancement coefficient according to a comparison result of the pixel mean value and a preset pixel threshold value, and determining that the enhancement coefficient is 1 when the comparison result is that the pixel mean value is not greater than the preset pixel threshold value; when the comparison result shows that the pixel mean value is larger than the preset pixel threshold value, determining that the enhancement coefficient is 1.5;
multiplying the enhancement coefficient by the frequency domain coefficient, and taking the product as the enhancement frequency domain coefficient;
and carrying out inverse transformation of multi-scale transformation on the pixel values of the second filtered image according to the enhanced frequency domain coefficient, and correcting each pixel value of the second filtered image according to the transformation result of the inverse transformation.
Preferably, the method for carbon sink statistics based on monitoring and evaluating carbon sink potential of mangrove ecological system constructs mangrove simulated ecological system according to ecological data, comprising:
based on ecological data, a virtual simulation model is built by utilizing three-dimensional modeling software, and a mangrove forest simulation ecological system is built according to the virtual simulation model.
Preferably, the influence factor information comprises predicted soil information, predicted climate information, predicted rainfall information and predicted plant change information based on a carbon sink statistical method of the mangrove ecological system carbon sink potential monitoring and evaluation.
Preferably, the carbon sink potential comprises plant carbon sink potential and soil carbon sink potential based on a carbon sink potential monitoring and evaluating method of the mangrove ecological system.
Preferably, the carbon sink potential monitoring and evaluating method based on the mangrove ecological system carbon sink potential monitoring and evaluating is used for carrying out carbon sink potential monitoring and evaluating according to influence factor information and current carbon sink potential, and determining a carbon sink potential evaluating result, and comprises the following steps:
determining environmental change information of the mangrove ecological system according to the predicted climate information and the predicted rainfall information;
based on a preset plant sample set and a temperature-specific method model, a plant growth prediction model is constructed, and predicted plant data determined according to predicted plant change information is input into the plant growth prediction model to obtain a plant growth prediction result;
dividing a mangrove ecological system into a plurality of grid areas;
determining plant distribution conditions of the mangrove ecological system in preset time according to plant growth prediction results, and determining forestation indexes of any area of the mangrove ecological system under the plant distribution conditions;
acquiring carbon-containing coefficients of different types of plants, and determining first prediction data of carbon sink potential of the area according to environmental change information, forestation indexes, the carbon-containing coefficients and current plant carbon sink potential obtained by monitoring;
determining second prediction data of carbon sink potential of the area according to the environmental change information, the predicted soil information and the current carbon sink potential of the soil obtained by monitoring;
and determining a carbon sink potential evaluation result of the area according to the first prediction data and the second prediction data, and performing the carbon sink potential evaluation processing process on all areas in the mangrove ecological system to obtain the carbon sink potential evaluation result of the mangrove ecological system.
According to the method, a mangrove forest simulation ecological system is constructed according to the acquired ecological data in the mangrove forest ecological system, carbon sink potential monitoring evaluation is carried out according to the acquired influence factor information and the current carbon sink potential, a carbon sink potential evaluation result is determined, and carbon sink is counted based on the evaluation result. Thereby realizing the technical effect of accurately and effectively counting carbon sinks in the mangrove ecological system.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a carbon sink statistics method based on monitoring and evaluating carbon sink potential of a mangrove ecosystem in an embodiment of the invention;
FIG. 2 is a flow chart of an alternative image preprocessing in an embodiment of the invention;
FIG. 3 is an alternative carbon sink statistics flow chart in accordance with an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Referring to fig. 1, an embodiment of the present invention provides a carbon sink statistics method based on monitoring and evaluating carbon sink potential of a mangrove ecological system, including:
step S1, ecological data in a mangrove ecological system are obtained;
s2, constructing a mangrove forest simulation ecological system according to ecological data;
step S3, adding influence factor information of carbon sink into the mangrove forest simulated ecological system, acquiring current carbon sink potential monitored in the mangrove forest simulated ecological system, and carrying out carbon sink potential monitoring evaluation according to the influence factor information and the current carbon sink potential to determine a carbon sink potential evaluation result;
and S4, counting carbon sinks based on the evaluation result.
In this embodiment, the specific implementation manner of adding the influence factor information of carbon sink in the mangrove forest simulated ecological system may be: and adding the acquired influence factor information of the carbon sink into the mangrove simulated ecological system through a data transmission unit of the mangrove simulated ecological system.
The technical principle of the technical scheme is as follows: acquiring ecological data in a mangrove ecological system; constructing a mangrove forest simulation ecological system according to the ecological data; adding carbon sink influence factor information into the mangrove forest simulated ecological system, acquiring current carbon sink potential monitored in the mangrove forest simulated ecological system, and carrying out carbon sink potential monitoring evaluation according to the influence factor information and the current carbon sink potential to determine a carbon sink potential evaluation result; and counting carbon sinks based on the evaluation result.
The technical effects of the technical scheme are as follows: constructing a mangrove forest simulation ecological system according to the acquired ecological data in the mangrove forest ecological system, carrying out carbon sink potential monitoring evaluation according to the acquired influence factor information and the current carbon sink potential, determining a carbon sink potential evaluation result, and carrying out statistics on carbon sinks based on the evaluation result. Thereby realizing the technical effect of accurately and effectively counting carbon sinks in the mangrove ecological system.
The embodiment of the invention provides a carbon sink statistical method based on monitoring and evaluating carbon sink potential of a mangrove ecological system, which comprises the following steps of:
acquiring three-dimensional coordinates, characteristic information and connection information of a plurality of terrain points in the mangrove ecological system, and determining terrain data of the mangrove ecological system according to the three-dimensional coordinates, the characteristic information and the connection information;
collecting images of the mangrove ecological system through a remote sensing technology, carrying out image preprocessing on the images, determining image information data, and taking the image information data as image data of the mangrove ecological system;
acquiring soil data of the mangrove ecological system by accessing a preset soil information database;
acquiring climate data of a mangrove forest ecosystem by accessing a preset climate database;
acquiring rainfall data of the mangrove forest ecosystem by accessing a preset rainfall database;
acquiring plant data of the mangrove ecological system by accessing a preset plant database;
and determining ecological data in the mangrove ecological system according to the terrain data, the image data, the soil data, the climate data, the rainfall data and the plant data.
In this embodiment, the method for obtaining three-dimensional coordinates, feature information and connection information of a plurality of terrain points in the mangrove ecological system and determining terrain data of the mangrove ecological system according to the three-dimensional coordinates, feature information and connection information may be as follows: the method comprises the steps of obtaining three-dimensional coordinates of terrain points in field measurement by using a measuring instrument, encoding the terrain points according to characteristics of the terrain points, obtaining connection information according to images of a mangrove ecological system, obtaining ground features according to the connection information and the three-dimensional coordinates, and determining terrain data of the mangrove ecological system according to a plurality of ground features and the encoded terrain points.
In this embodiment, the specific implementation manner of obtaining the soil data of the mangrove ecological system by accessing the preset soil information database may be: and connecting the data acquisition equipment with a preset soil information database, and acquiring soil data of the mangrove ecological system through the data acquisition equipment.
In this embodiment, the soil information database stores soil information of years of the mangrove ecosystem, the climate database stores climate information of years of the mangrove ecosystem, and the rainfall database stores rainfall information of years of the mangrove ecosystem, and the plant database stores plant data of years of the mangrove ecosystem.
The technical principle of the technical scheme is as follows: acquiring three-dimensional coordinates, characteristic information and connection information of a plurality of terrain points in the mangrove ecological system, and determining terrain data of the mangrove ecological system according to the three-dimensional coordinates, the characteristic information and the connection information; collecting images of the mangrove ecological system through a remote sensing technology, carrying out image preprocessing on the images, determining image information data, and taking the image information data as image data of the mangrove ecological system; acquiring soil data of the mangrove ecological system by accessing a preset soil information database; acquiring climate data of a mangrove forest ecosystem by accessing a preset climate database; acquiring rainfall data of the mangrove forest ecosystem by accessing a preset rainfall database; acquiring plant data of the mangrove ecological system by accessing a preset plant database; and determining ecological data in the mangrove ecological system according to the terrain data, the image data, the soil data, the climate data, the rainfall data and the plant data.
The technical effects of the technical scheme are as follows: by collecting the ecological data of the mangrove ecological system, a data base is provided for the subsequent construction of the simulated ecological system, so that the constructed simulated ecological system is more accurate and real.
Referring to fig. 2, an embodiment of the present invention provides a carbon sink statistics method based on monitoring and evaluating carbon sink potential of a mangrove ecological system, which collects images of the mangrove ecological system through a remote sensing technology, performs image preprocessing on the images, determines image information data, uses the image information data as image data of the mangrove ecological system, and includes:
step S121, acquiring an image of a mangrove ecological system through a remote sensing technology, and taking the image as a first image;
step S122, inputting the first image into a pre-trained image feature extraction network, extracting features of the first image to obtain a feature region, marking the feature region, and determining the image after region marking as a second image;
step S123, performing noise reduction processing on the second image to obtain a third image;
step S124, sharpening the third image to obtain a fourth image, determining image information data of the fourth image, and taking the image information data as image data of the mangrove ecological system.
In this embodiment, the specific implementation manner of inputting the first image into the pre-trained image feature extraction network, extracting features of the first image to obtain a feature region, marking the feature region, and determining the image after the region marking as the second image may be: and performing feature extraction network training according to the existing image set and the image set subjected to feature extraction, inputting the first image into an image feature extraction network, determining a feature area of the first image according to an output result of the feature extraction network, performing fluorescent marking on the feature area, and determining the image subjected to fluorescent marking as a second image.
In this embodiment, the specific implementation manner of sharpening the third image to obtain the fourth image may be: acquiring pixel values of all pixel points of the point image, and determining a pixel mean value of a third image according to the pixel values of all pixel points; selecting any pixel point of the third image as a central pixel point, taking the central pixel point as a circle center, presetting a side length r (r is smaller than the length and the width of the third image) as a radius to define a circular area, and calculating the pixel mean value of the pixel points in the area; determining a first sharpening intensity according to the pixel mean value of the third image and the pixel mean value of the pixel points in the region; acquiring gradient values of all pixel points of the point image, and determining a gradient mean value of a third image according to the pixel values of all pixel points; calculating the gradient mean value of the pixel points in the region; determining second sharpening strength according to the gradient mean value of the third image and the gradient mean value of the pixel points in the region; and correcting the pixels of the central pixel point according to the first sharpening intensity and the second sharpening intensity, and performing the above operation on all the pixel points of the third image to obtain a fourth image.
The technical principle of the technical scheme is as follows: collecting an image of a mangrove ecological system through a remote sensing technology, and taking the image as a first image; inputting the first image into a pre-trained image feature extraction network, carrying out feature extraction on the first image to obtain a feature region, marking the feature region, and determining the image subjected to region marking as a second image; noise reduction processing is carried out on the second image, and a third image is obtained; and carrying out sharpening processing on the third image to obtain a fourth image, determining image information data of the fourth image, and taking the image information data as image data of the mangrove ecological system.
The technical effects of the technical scheme are as follows: the preprocessing of the image improves the definition of the image, highlights the characteristic information of the image, is beneficial to identifying the information in the mangrove ecological system, and saves the time for constructing a simulation system subsequently.
The embodiment of the invention provides a carbon sink statistical method based on monitoring and evaluating carbon sink potential of a mangrove ecological system, which carries out noise reduction treatment on a second image to obtain a third image, and comprises the following steps:
respectively carrying out wiener filtering processing and Laplace filtering processing on the second image to obtain a first filtering image and a second filtering image;
image segmentation is carried out on the first filtering image to obtain a plurality of segmentation areas;
selecting any divided area, determining the midpoint of the divided area as a central pixel point, calculating the difference between gray values of the pixel points adjacent to the central pixel point in eight directions and the central pixel point, determining a correction matrix according to the difference between the gray values, the second image and the first filter image, and determining a gray correction value of the central pixel point according to the matrix characteristic value of the correction matrix;
correcting the pixel value of the central pixel point according to the gray correction value, and performing the above operation on all the pixel points in all the divided areas to obtain a first corrected image;
acquiring pixel values of all pixel points of the second filter image, and calculating a pixel mean value of the second filter image according to the pixel values of all pixel points;
performing multi-scale geometric transformation on the second filter image to obtain a frequency domain coefficient of the second filter image;
correcting each pixel value of the second filter image according to the pixel mean value and the frequency domain coefficient to obtain a second corrected image;
and carrying out image fusion on the first corrected image and the second corrected image to obtain a fused image, and taking the fused image as a third image.
In this embodiment, the specific implementation manner of performing image segmentation on the first filtered image to obtain a plurality of segmented regions may be: and performing model training according to the existing image set and the existing segmented image set to obtain an image segmentation model, and inputting the first filtered image into the image segmentation model to obtain a plurality of segmentation areas.
In this embodiment, the multi-scale transform may be a wavelet transform, a curvilinear wave transform, a non-downsampled laplace tower transform, or the like.
In this embodiment, the specific implementation manner of performing multi-scale geometric transformation on the second filtered image to obtain the frequency domain coefficient of the second filtered image may be: gradually carrying out multi-scale refinement on the signal function of the second filtered image through expansion Ping Yiyun calculation, decomposing the signal function of the second filtered image from different scales to obtain coefficients of the signal function under different scales, and averaging the coefficients under different scales to obtain the frequency domain coefficients of the second filtered image.
The technical principle of the technical scheme is as follows: respectively carrying out wiener filtering processing and Laplace filtering processing on the second image to obtain a first filtering image and a second filtering image; image segmentation is carried out on the first filtering image to obtain a plurality of segmentation areas; selecting any divided area, determining the middle point of the divided area as a central pixel point, calculating the difference between gray values of the pixel points adjacent to the central pixel point in eight directions and the central pixel point, determining a correction matrix according to the difference between the gray values and the minimum mean square error of wiener filtering, and determining the gray correction value of the central pixel point according to the matrix characteristic value of the correction matrix; correcting the pixel value of the central pixel point according to the gray correction value, and performing the above operation on all the pixel points in all the divided areas to obtain a first corrected image; acquiring pixel values of all pixel points of the second filter image, and calculating a pixel mean value of the second filter image according to the pixel values of all pixel points; performing multi-scale geometric transformation on the second filter image to obtain a frequency domain coefficient of the second filter image; correcting each pixel value of the second filter image according to the pixel mean value and the frequency domain coefficient to obtain a second corrected image; and carrying out image fusion on the first corrected image and the second corrected image to obtain a fused image, and taking the fused image as a third image.
The technical effects of the technical scheme are as follows: the images obtained by the second image through different filtering modes are fused, the beneficial information of the images is extracted to the maximum extent while the noise reduction is finished, the quality of the images is improved, and the utilization rate of the image information is further improved.
The embodiment of the invention provides a carbon sink statistical method based on monitoring and evaluating carbon sink potential of a mangrove ecological system, which comprises the steps of determining a correction matrix according to the difference of gray values, a second image and a first filter image, determining a gray correction value of a central pixel point according to a matrix characteristic value of the correction matrix, and comprising the following steps:
determining a minimum mean square error according to the second image and the first filtered image;
taking the opposite number from the square of the difference between the gray values of the central pixel point and the adjacent pixel points, dividing the opposite number by 2 times of the square of the minimum mean square error, and determining a first coefficient;
performing exponential operation on the first coefficient to determine a second coefficient;
multiplying the minimum mean square error with a preset coefficient, taking the reciprocal of the multiplied result, and determining a third coefficient;
taking the product obtained by multiplying the second coefficient and the third coefficient as a matrix element in the correction matrix, and performing the operation on each adjacent pixel point to determine the correction matrix;
and calculating a matrix characteristic value of the correction matrix, and taking the average value of the matrix characteristic value as a gray correction value of the central pixel point.
In this embodiment, a specific implementation manner of determining the minimum mean square error according to the second image and the first filtered image may be: calculating the variance of pixel values of the A pixel point of the second image and the A pixel point of the first filter image, taking the variance as one of elements of a variance set, carrying out variance calculation on each pixel point of the second image and the first filter image to obtain the variance set, calculating the mean value of variances in the variance set, and taking the mean value as the minimum mean square error.
In this embodiment, a specific implementation manner of performing the exponential operation on the first coefficient to determine the second coefficient may be: setting the exponential function to y=e x Substituting the first coefficient into the exponential function as the value of the argument x, and taking the calculated result as the second coefficient.
In this embodiment, the preset coefficient may be a value obtained by a 2pi open root number.
The technical principle of the technical scheme is as follows: determining a minimum mean square error according to the second image and the first filtered image; taking the opposite number from the square of the difference between the gray values of the central pixel point and the adjacent pixel points, dividing the opposite number by 2 times of the square of the minimum mean square error, and determining a first coefficient; performing exponential operation on the first coefficient to determine a second coefficient; multiplying the minimum mean square error with a preset coefficient, taking the reciprocal of the multiplied result, and determining a third coefficient; taking the product obtained by multiplying the second coefficient and the third coefficient as a matrix element in the correction matrix, and performing the operation on each adjacent pixel point to determine the correction matrix; and calculating a matrix characteristic value of the correction matrix, and taking the average value of the matrix characteristic value as a gray correction value of the central pixel point.
The technical effects of the technical scheme are as follows: the noise reduction of the first filtered image is completed by correcting the gray value of the first filtered image, so that the image information of the first filtered image is clearer.
The embodiment of the invention provides a carbon sink statistical method based on monitoring and evaluating carbon sink potential of a mangrove ecological system, which corrects each pixel value of a second filtering image according to a pixel mean value and a frequency domain coefficient, and comprises the following steps:
determining an enhancement coefficient according to a comparison result of the pixel mean value and a preset pixel threshold value, and determining that the enhancement coefficient is 1 when the comparison result is that the pixel mean value is not greater than the preset pixel threshold value; when the comparison result shows that the pixel mean value is larger than the preset pixel threshold value, determining that the enhancement coefficient is 1.5;
multiplying the enhancement coefficient by the frequency domain coefficient, and taking the product as the enhancement frequency domain coefficient;
and carrying out inverse transformation of multi-scale transformation on the pixel values of the second filtered image according to the enhanced frequency domain coefficient, and correcting each pixel value of the second filtered image according to the transformation result of the inverse transformation.
The technical principle of the technical scheme is as follows: determining an enhancement coefficient according to a comparison result of the pixel mean value and a preset pixel threshold value; performing enhancement calculation on the frequency domain coefficients based on the enhancement coefficients to obtain enhancement frequency domain coefficients; and carrying out inverse transformation of multi-scale transformation on the pixel values of the second filtered image according to the enhanced frequency domain coefficient, and correcting each pixel value of the second filtered image according to the transformation result of the inverse transformation.
The technical effects of the technical scheme are as follows: and correcting the pixel value of the second filtered image through the enhancement coefficient and the multi-scale inverse transformation, so that the noise reduction of the second filtered image is completed, and the image information of the second filtered image is clearer.
The embodiment of the invention provides a carbon sink statistical method based on monitoring and evaluating carbon sink potential of a mangrove ecological system, which constructs the mangrove simulated ecological system according to ecological data and comprises the following steps:
based on ecological data, a virtual simulation model is built by utilizing three-dimensional modeling software, and a mangrove forest simulation ecological system is built according to the virtual simulation model.
The technical principle of the technical scheme is as follows: based on ecological data, constructing a virtual simulation model of the mangrove ecological system by utilizing three-dimensional modeling software; designing an information acquisition component based on the pre-acquired demand; and constructing a mangrove forest simulation ecological system according to the virtual simulation model and the information acquisition component.
The technical effects of the technical scheme are as follows: real-time monitoring and data transmission of the mangrove ecological system can be realized by constructing the mangrove simulated ecological system, so that the time is saved, and the statistical efficiency is improved.
The embodiment of the invention provides a carbon sink statistical method based on monitoring and evaluating carbon sink potential of a mangrove ecological system, and influence factor information comprises predicted soil information, predicted climate information, predicted rainfall information and predicted plant change information.
Referring to fig. 3, an embodiment of the invention provides a carbon sink statistics method based on monitoring and evaluating carbon sink potential of mangrove ecosystem, wherein the carbon sink potential comprises plant carbon sink potential and soil carbon sink potential.
The embodiment of the invention provides a carbon sink potential monitoring and evaluating method based on a mangrove ecological system, which carries out carbon sink potential monitoring and evaluating according to influence factor information and current carbon sink potential to determine a carbon sink potential evaluating result and comprises the following steps:
step S31, determining environmental change information of the mangrove ecological system according to the predicted climate information and the predicted rainfall information;
step S32, a plant growth prediction model is constructed based on a preset plant sample set and a temperature-specific method model, and predicted plant data determined according to predicted plant change information is input into the plant growth prediction model to obtain a plant growth prediction result;
step S33, dividing the mangrove ecological system into a plurality of grid areas;
step S34, determining the plant distribution condition of the mangrove ecological system in preset time according to the plant growth prediction result, and determining the forestation index of any area of the mangrove ecological system under the plant distribution condition;
step S35, obtaining carbon-containing coefficients of different types of plants, and determining first prediction data of carbon sink potential of the area according to environmental change information, forestation indexes, carbon-containing coefficients and current plant carbon sink potential obtained by monitoring;
step S36, determining second predicted data of carbon sink potential of the area according to the environmental change information, the predicted soil information and the current carbon sink potential obtained by monitoring;
and step S37, determining a carbon sink potential evaluation result of the area according to the first prediction data and the second prediction data, and performing the carbon sink potential evaluation processing process on all areas in the mangrove ecological system to obtain the carbon sink potential evaluation result of the mangrove ecological system.
In this embodiment, based on the preset plant sample set and the temperature-specific method model, a specific implementation manner of constructing the plant growth prediction model may be: the method comprises the steps of presetting tree species, tree breast diameters, tree numbers and tree heights of plant samples stored in a plant sample set, predicting the tree species, tree breast diameters, tree numbers and tree heights based on a temperature-t method model according to information stored in the plant sample set, performing model training based on the plant sample set and data obtained through prediction, and constructing a plant growth prediction model.
In this embodiment, a specific implementation of dividing the mangrove ecosystem into a plurality of grid areas may be: dividing the mangrove ecological system into a plurality of square grid areas with similar sizes according to the image data of the mangrove ecological system.
In this example, a specific embodiment of determining the forestation index for any area of the mangrove ecosystem in the case of plant distribution may be: and (3) making a difference between the plant number of any area of the mangrove ecological system and the plant number of the area of the current mangrove ecological system at preset time, and comparing the difference with the plant number of the area of the current mangrove ecological system to obtain a ratio which is the forestation index of the area.
In this embodiment, the specific implementation of the first prediction data for determining the carbon sink potential of the area according to the environmental change information, the forestation index, the carbon content coefficient and the current plant carbon sink potential obtained by monitoring may be: and training a first prediction model according to the existing environmental information, forestation indexes, carbon-containing coefficients and plant carbon sink potential data, continuously optimizing model parameters in the training process, inputting the environmental change information, forestation indexes, carbon-containing coefficients and the current plant carbon sink potential obtained by monitoring into the trained first prediction model, and taking the output result of the first prediction model as the first prediction data.
In this embodiment, the specific implementation manner of determining the second predicted data of the carbon sink potential of the area according to the environmental change information, the predicted soil information and the current carbon sink potential obtained by monitoring may be: and training a second prediction model according to the existing environmental information, soil information and carbon sink potential data, continuously optimizing model parameters in the training process, inputting the environmental change information, the predicted soil information and the current carbon sink potential of the soil obtained by monitoring into the trained second prediction model, and taking the output result of the second prediction model as second prediction data.
In this embodiment, the specific implementation of determining the carbon sink potential evaluation result of the area according to the first prediction data and the second prediction data may be: and adding the first prediction data and the second prediction data, and taking the obtained result as a carbon sink potential evaluation result of the region.
The technical principle of the technical scheme is as follows: determining environmental change information of the mangrove ecological system according to the predicted climate information and the predicted rainfall information; based on a preset plant sample set and a temperature-specific method model, a plant growth prediction model is constructed, and predicted plant data determined according to predicted plant change information is input into the plant growth prediction model to obtain a plant growth prediction result; dividing a mangrove ecological system into a plurality of grid areas; determining plant distribution conditions of the mangrove ecological system in preset time according to plant growth prediction results, and determining forestation indexes of any area of the mangrove ecological system under the plant distribution conditions; acquiring carbon-containing coefficients of different types of plants, and determining first prediction data of carbon sink potential of the area according to environmental change information, forestation indexes, the carbon-containing coefficients and current plant carbon sink potential obtained by monitoring; determining second prediction data of carbon sink potential of the area according to the environmental change information, the predicted soil information and the current carbon sink potential of the soil obtained by monitoring; and determining a carbon sink potential evaluation result of the area according to the first prediction data and the second prediction data, and performing the carbon sink potential evaluation processing process on all areas in the mangrove ecological system to obtain the carbon sink potential evaluation result of the mangrove ecological system.
The technical effects of the technical scheme are as follows: the carbon sink potential of the mangrove ecological system and the carbon sink potential of the soil are predicted to obtain a carbon sink potential evaluation result of the mangrove ecological system, and the technical effect of accurately and effectively counting the carbon sink of the mangrove ecological system is achieved based on the carbon sink potential evaluation result.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A carbon sink statistical method based on monitoring and evaluating carbon sink potential of mangrove ecosystem, comprising:
acquiring ecological data in a mangrove ecological system;
constructing a mangrove forest simulation ecological system according to the ecological data;
adding carbon sink influence factor information into the mangrove forest simulated ecological system, acquiring current carbon sink potential monitored in the mangrove forest simulated ecological system, and carrying out carbon sink potential monitoring evaluation according to the influence factor information and the current carbon sink potential to determine a carbon sink potential evaluation result;
and counting carbon sinks based on the evaluation result.
2. The method for carbon sink statistics based on monitoring and assessing carbon sink potential of a mangrove ecosystem as recited in claim 1, wherein obtaining ecological data in the mangrove ecosystem comprises:
three-dimensional coordinates, characteristic information and connection information of a plurality of terrain points in the mangrove ecological system are obtained, and terrain data of the mangrove ecological system are determined according to the three-dimensional coordinates, the characteristic information and the connection information;
acquiring an image of the mangrove ecological system through a remote sensing technology, performing image preprocessing on the image, determining image information data, and taking the image information data as image data of the mangrove ecological system;
acquiring soil data of the mangrove ecological system by accessing a preset soil information database;
acquiring climate data of the mangrove ecological system by accessing a preset climate database;
acquiring rainfall data of the mangrove forest ecosystem by accessing a preset rainfall database;
acquiring plant data of the mangrove ecological system by accessing a preset plant database;
and determining ecological data in the mangrove ecological system according to the terrain data, the image data, the soil data, the climate data, the rainfall data and the plant data.
3. The method for carbon sink statistics based on monitoring and evaluating carbon sink potential of mangrove ecosystem as set forth in claim 2, wherein collecting images of the mangrove ecosystem by remote sensing technology, performing image preprocessing on the images, determining image information data, and using the image information data as image data of the mangrove ecosystem includes:
acquiring an image of the mangrove ecological system through a remote sensing technology, and taking the image as a first image;
inputting the first image into a pre-trained image feature extraction network, carrying out feature extraction on the first image to obtain a feature region, marking the feature region, and determining the image subjected to region marking as a second image;
carrying out noise reduction treatment on the second image to obtain a third image;
and carrying out sharpening processing on the third image to obtain a fourth image, determining image information data of the fourth image, and taking the image information data as image data of the mangrove ecological system.
4. The method for carbon sink statistics based on monitoring and evaluating carbon sink potential of mangrove ecosystem as set forth in claim 3, wherein the noise reduction processing is performed on the second image to obtain a third image, comprising:
respectively carrying out wiener filtering processing and Laplace filtering processing on the second image to obtain a first filtering image and a second filtering image;
image segmentation is carried out on the first filtering image to obtain a plurality of segmentation areas;
selecting any divided area, determining the midpoint of the divided area as a central pixel point, calculating the difference between gray values of the pixel points adjacent to the central pixel point in eight directions and the central pixel point, determining a correction matrix according to the difference between the gray values, the second image and the first filter image, and determining a gray correction value of the central pixel point according to the matrix characteristic value of the correction matrix;
correcting the pixel value of the central pixel point according to the gray correction value, and performing the above operation on all the pixel points in all the divided areas to obtain a first corrected image;
acquiring pixel values of all pixel points of the second filter image, and calculating a pixel mean value of the second filter image according to the pixel values of all pixel points;
performing multi-scale geometric transformation on the second filtered image to obtain a frequency domain coefficient of the second filtered image;
correcting each pixel value of the second filter image according to the pixel mean value and the frequency domain coefficient to obtain a second corrected image;
and carrying out image fusion on the first corrected image and the second corrected image to obtain a fused image, and taking the fused image as a third image.
5. The method for carbon sink statistics based on mangrove ecosystem carbon sink potential monitoring and assessment according to claim 4, wherein determining a correction matrix based on the difference in gray values, the second image and the first filtered image, and determining a gray correction value for the center pixel based on a matrix eigenvalue of the correction matrix, comprises:
determining a minimum mean square error according to the second image and the first filtered image;
taking the opposite number from the square of the difference between the gray values of the central pixel point and the adjacent pixel points, dividing the opposite number by 2 times of the square of the minimum mean square error, and determining a first coefficient;
performing exponential operation on the first coefficient to determine a second coefficient;
multiplying the minimum mean square error with a preset coefficient, taking the reciprocal of the multiplied result, and determining a third coefficient;
taking the product obtained by multiplying the second coefficient and the third coefficient as a matrix element in a correction matrix, and performing the above operation on each adjacent pixel point to determine the correction matrix;
and calculating a matrix characteristic value of the correction matrix, and taking the average value of the matrix characteristic value as a gray correction value of the central pixel point.
6. The method of carbon sink statistics based on mangrove ecosystem carbon sink potential monitoring and assessment of claim 4, wherein modifying each pixel value of the second filtered image based on the pixel mean and the frequency domain coefficients comprises:
determining an enhancement coefficient according to a comparison result of the pixel mean value and a preset pixel threshold value, and determining that the enhancement coefficient is 1 when the comparison result is that the pixel mean value is not greater than the preset pixel threshold value; when the comparison result shows that the pixel mean value is larger than the preset pixel threshold value, determining that the enhancement coefficient is 1.5;
multiplying the enhancement coefficient by the frequency domain coefficient, and taking the product as the enhancement frequency domain coefficient;
and carrying out inverse transformation of multi-scale transformation on the pixel values of the second filtered image according to the enhanced frequency domain coefficients, and correcting each pixel value of the second filtered image according to the transformation result of the inverse transformation.
7. The method for carbon sink statistics based on monitoring and assessing carbon sink potential of mangrove ecosystem as recited in claim 1, wherein constructing a mangrove simulated ecosystem from the ecological data includes:
based on the ecological data, a virtual simulation model is built by utilizing three-dimensional modeling software, and a mangrove forest simulation ecological system is built according to the virtual simulation model.
8. The method for carbon sink statistics based on monitoring and assessing carbon sink potential of mangrove ecosystem as recited in claim 1, wherein the influencing factor information includes predicted soil information, predicted climate information, predicted rainfall information, and predicted plant change information.
9. The method for carbon sink statistics based on monitoring and assessing carbon sink potential of mangrove ecosystem as claimed in claim 1, wherein the carbon sink potential comprises plant carbon sink potential and soil carbon sink potential.
10. The method for carbon sink statistics based on monitoring and evaluating carbon sink potential of mangrove ecosystem as set forth in claim 8, wherein the performing the monitoring and evaluating carbon sink potential based on the influence factor information and the current carbon sink potential to determine the carbon sink potential evaluation result comprises:
determining environmental change information of the mangrove ecological system according to the predicted climate information and the predicted rainfall information;
based on a preset plant sample set and a temperature-specific method model, a plant growth prediction model is constructed, and predicted plant data determined according to predicted plant change information is input into the plant growth prediction model to obtain a plant growth prediction result;
dividing a mangrove ecological system into a plurality of grid areas;
determining plant distribution conditions of the mangrove ecological system in preset time according to plant growth prediction results, and determining forestation indexes of any area of the mangrove ecological system under the plant distribution conditions;
acquiring carbon-containing coefficients of different types of plants, and determining first prediction data of carbon sink potential of the area according to the environmental change information, forestation indexes, the carbon-containing coefficients and current plant carbon sink potential obtained by monitoring;
determining second prediction data of carbon sink potential of the area according to the environmental change information, the predicted soil information and the current carbon sink potential of the soil obtained by monitoring;
and determining a carbon sink potential evaluation result of the area according to the first prediction data and the second prediction data, and performing the carbon sink potential evaluation processing process on all areas in the mangrove ecological system to obtain the carbon sink potential evaluation result of the mangrove ecological system.
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